Image processing tasks include automated image editing tasks such as in-painting, and de-noising as well as computer vision tasks which typically involve processing images captured from the real world in order to interpret the information in those images. An example is calculating joint positions in images of people in order to understand how a person, such as someone playing a computer game, is oriented and positioned in an environment. Computer vision tasks, such as calculating a person's joint positions or other features of an image is useful for many application including but not limited to: computer games, augmented reality, human-computer interaction, sensing and control applications, robotics, medical applications and others.
Existing approaches to joint position estimation typically comprise identifying body parts in images of a person by using trained machine learning systems and then fitting a skeletal model to the body parts. Other approaches have involved calculating joint positions from images of a person again using trained machine learning systems. There is ongoing need to improve the accuracy and robustness of existing systems.
The embodiments described below are not limited to implementations which solve any or all of the disadvantages of known image processing systems.